Part-Time Gaia Variable Star ML Researcher

University of North Carolina at Chapel Hill; Chapel Hill (NC); On-site; USD 30,000 - 42,000; Part time

Benefits offered by this job

Discounts at local retailers

Child care discounts

Special rates for performing arts

Job summary

The University of North Carolina at Chapel Hill, Department of Physics and Astronomy, seeks a part-time Research Assistant to support the Gaia in Technicolor project using machine learning to map variability of stars. You will work under Dr. Barlow and Dr.

Zikry on classification of Gaia DR3 photometry and HR diagram motions, with 30 hours per week and a 10:00 AM–4:30 PM schedule. This temporary role runs 1–6 months, starts January 4, 2027, and offers the opportunity to gain hands-on experience

Qualifications

• Experience with Gaia DR3 multi-epoch photometry or HR diagram analysis.
• Experience with functional data analysis, smoothing splines, or unsupervised clustering methods.
• Familiarity with high-performance computing (e.g., UNC Longleaf) or GPU cloud computing resources.
• Experience with time-domain survey data (e.g., TESS, ZTF, ASAS-SN) or variable star astrophysics.

Responsibilities

• Serve as the primary day-to-day researcher for the Gaia in Technicolor project, under supervision of Barlow and Zikry.
• Support discovery, characterization, and dissemination of results.
• Collaborate to develop interactive data visualizations and analysis workflows.

Skills

Gaia DR3 data analysis

Functional data analysis

Time-domain astronomy

Tools

Longleaf HPC

GPU cloud computing

Interactive web visualization tools

Job description

The University of North Carolina at Chapel Hill, Department of Physics and Astronomy, seeks a part-time Research Assistant to support the Gaia in Technicolor project using machine learning to map variability of stars. You will work under Dr. Barlow and Dr.

Zikry on classification of Gaia DR3 photometry and HR diagram motions, with 30 hours per week and a 10:00 AM–4:30 PM schedule. This temporary role runs 1–6 months, starts January 4, 2027, and offers the opportunity to gain hands-on experience